AdamCodd/YOLOv11x-face-detection
By AdamCodd · ↓ 11 · ♥ 3 · Updated 2025-08-28
What's in this repo
This page lists the files in AdamCodd/YOLOv11x-face-detection, including model.onnx.
- 1 ONNX models (.onnx files)
- 11 files, including 6 .png, 1 .md, 1 .json, 1 .onnx, 1 .pt
- Last updated 2025-08-28
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
YOLOv11x-Face-Detection
A lightweight face detection model based on YOLO architecture (YOLOv11 xlarge), trained for 100 epochs on the WIDERFACE dataset. It's way more accurate than my YOLOv11n model, but slower.
It achieves the following results on the evaluation set:
==================== Results ====================
Easy Val AP: 0.9629194049702874
Medium Val AP: 0.9519172409689101
Hard Val AP: 0.8800338681974709
=================================================
YOLO results:
[[27338 3110]
[12337 0]]
Usage
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
model_path = hf_hub_download(repo_id="AdamCodd/YOLOv11x-face-detection", filename="model.pt")
model = YOLO(model_path)
results = model.predict("/path/to/your/image", save=True) # saves the result in runs/detect/predict
Limitations
- Performance may vary in extreme lighting conditions
- Best suited for frontal and slightly angled faces
- Optimal performance for faces occupying >20 pixels
Model info
Created: 2025-08-28
Updated: 2025-08-28
View on Hugging Face